docstr: Builds training graph for discriminator
  Arguments:
       disc_pred(object): Discriminator instance
docstr_tok: ["Builds","training","graph","for","discriminator","Arguments",":","disc_pred","(","object",")",":","Discriminator","instance"]
code: def build_train_graph(self, disc_pred):
      """
      Builds training graph for discriminator
      Arguments:
           disc_pred(object): Discriminator instance
      """
      # Variables in discrimnator scope
      disc_vars = tf.get_collection(
          tf.GraphKeys.TRAINABLE_VARIABLES, "Discriminator"
      )
      # Binary Cross entropy
      disc_entropy = tf.nn.sigmoid_cross_entropy_with_logits(
          logits=disc_pred, labels=self.Y
      )
      # Cost
      self.disc_cost = tf.reduce_mean(disc_entropy)
      # Optimizer
      disc_opt = tf.train.GradientDescentOptimizer(self.lr_ph)
      self.disc_opt = disc_opt.minimize(
          self.disc_cost, var_list=disc_vars
      )
  
imports: from __future__ import print_function, division
  import io
  import os
  import time
  import numpy
  import scipy
  import tensorflow
label_desc: Use image node_id 3 for calling the Discriminator obj's underlying member method code with example usage: obj.build_train_graph(disc_pred) without return types